Automatic Text Simplification in Spanish: A Comparative Evaluation of Complementing Modules

In this paper we present two components of an automatic text simplification system for Spanish, aimed at making news articles more accessible to readers with cognitive disabilities. Our system in its current state consists of a rule-based lexical transformation component and a module for syntactic simplification. We evaluate the two components separately and as a whole, with a view to determining the level of simplification and the preservation of meaning and grammaticality. In order to test the readability level pre- and post-simplification, we apply seven readability measures for Spanish to three sets of randomly chosen news articles: the original texts, the output obtained after lexical transformations, the syntactic simplification output, and the output of both system components. To test whether the simplification output is grammatically correct and semantically adequate, we ask human annotators to grade pairs of original and simplified sentences according to these two criteria. Our results suggest that both components of our system produce simpler output when compared to the original, and that grammaticality and meaning preservation are positively rated by the annotators.